Selection of key video frames is useful in many applications. For example, it is often desirable to extract and present some subset of video data that can convey an accurate and recognizable summary or synopsis of the video. Key frame extraction algorithms are used to select a subset of the most informative frames from a video, with the goal of representing the most significant content of the video with a limited number of frames. Key frame extraction finds applications in several broad areas of video processing such as video summarization, creating chapter titles in DVDs, video indexing, and making prints from video. Summaries or synopses can also facilitate video sharing or help a user decide whether a full video is worth downloading or viewing. Key frame extraction is an active research area, and many approaches for extracting key frames from videos exist.
Algorithms for creating a video summary by extracting key video frames are known in the art. For example, U.S. Pat. No. 8,599,313 to Aaron T. Deever, which is incorporated herein by reference in its entirety, determines key video frames based primarily on inter-frame motion detection. U.S. Pat. No. 8,031,775 to J. Luo, et al., entitled analyzing camera captured video for key frames, which is incorporated herein by reference in its entirety, teaches the use of a camera's motion sensor, e.g., an accelerometer or a lens motor sensor, to estimate global motion, including translation of the scene or camera, or scaling of the scene. Key frames candidates are extracted from the video segment using a confidence score. U.S. Pat. No. 7,889,794 to J. Luo, et al., entitled Extracting Key Frame Candidates From Video Clip, which is incorporated herein by reference in its entirety, analyzes a video clip to determine key frames by performing a global motion estimate on the video clip that indicates translation of a scene or camera. As an additional example, U.S. Pat. No. 7,184,100, to I. Wilf, et al., entitled Method of selecting key-frames from a video sequence, which is also incorporated herein by reference in its entirety, teaches the selection of key frames from a video sequence by comparing each frame in the video sequence with the adjacent frames using both region and motion analysis. However, none of these references teaches using the extracted key frames to product printed output products based on certain characteristics of the key frames.
U.S. Patent Publication No. 2006/0257048 to X. Lin, et al., which is incorporated herein by reference in its entirety, teaches a method for automatically producing a printed page using frames of a video stream. The application teaches the use of a key frame extraction algorithm to extract key frames from a video sequence. Then a page layout workflow is described to automatically place the extracted key frames onto a page with user input. However, the application fails to teach how to infer and create different output product types (such as a video action print, panoramic print, and electronic slideshow).
As such, it would be useful to have methods to use information, such as motion characteristics and information regarding the amount of zoom used to capture a particular key frame, to select an output product type most suited to the characteristics of a particular key frame.